[R] A question on Unit Root Test using "urca" toolbox

Pfaff, Bernhard Dr. Bernhard_Pfaff at fra.invesco.com
Fri Feb 3 09:40:02 CET 2012


Hello Miao,

short answer: different sample sizes are used in your tests. 
long answer: in your first instance, the common sample size is determined for the allowance of 12 lags such that one is not comparing test results derived from different sample sizes. And hence, in your second instance, a longer sample size has been used.

Best,
Bernhard

-----Ursprüngliche Nachricht-----
Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im Auftrag von jpm miao
Gesendet: Freitag, 3. Februar 2012 08:45
An: r-help at r-project.org
Betreff: [R] A question on Unit Root Test using "urca" toolbox

Hello,

   I have a question on unit root test with urca toolbox.

   First, to run a unit root test with lags selected by BIC, I type:

> CPILD4UR<-ur.df(x1$CPILD4[5:nr1], type ="drift", lags=12, selectlags 
> ="BIC")
> summary(CPILD4UR)

   The results indicate that the optimal lags selected by BIC is 4.

   Then I run the same unit root test with drift and 4 lags:

> CPILD4UR1<-ur.df(x1$CPILD4[5:nr1], type ="drift", lags =4)
> summary(CPILD4UR1)

   Nevertheless, the results are different. Could anyone tells me why?
   In EViews these two are the same and the results are close to my first case.

    Thanks!

A complete log:

> CPILD4UR1<-ur.df(x1$CPILD4[5:nr1], type ="drift", lags =4)
> summary(CPILD4UR1)

###############################################
# Augmented Dickey-Fuller Test Unit Root Test # ###############################################

Test regression drift


Call:
lm(formula = z.diff ~ z.lag.1 + 1 + z.diff.lag)

Residuals:
     Min       1Q   Median       3Q      Max
-2.43555 -0.63440 -0.03048  0.53522  2.84237

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.238631   0.137262   1.739 0.084944
z.lag.1     -0.153030   0.061841  -2.475 0.014881
z.diff.lag1  0.011463   0.090330   0.127 0.899252
z.diff.lag2  0.008764   0.089850   0.098 0.922479
z.diff.lag3  0.149529   0.088930   1.681 0.095546
z.diff.lag4 -0.349870   0.088847  -3.938 0.000145

(Intercept) .
z.lag.1     *
z.diff.lag1
z.diff.lag2
z.diff.lag3 .
z.diff.lag4 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.9526 on 109 degrees of freedom
Multiple R-squared: 0.2514,	Adjusted R-squared: 0.2171
F-statistic: 7.321 on 5 and 109 DF,  p-value: 5.989e-06


Value of test-statistic is: -2.4746 3.0877

Critical values for test statistics:
      1pct  5pct 10pct
tau2 -3.46 -2.88 -2.57
phi1  6.52  4.63  3.81

> CPILD4UR<-ur.df(x1$CPILD4[5:nr1], type ="drift", lags=12, selectlags 
> ="BIC")
> summary(CPILD4UR)

###############################################
# Augmented Dickey-Fuller Test Unit Root Test # ###############################################

Test regression drift


Call:
lm(formula = z.diff ~ z.lag.1 + 1 + z.diff.lag)

Residuals:
    Min      1Q  Median      3Q     Max
-2.2551 -0.6335 -0.0372  0.5189  2.8249

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.250966   0.141141   1.778 0.078392
z.lag.1     -0.141102   0.062614  -2.254 0.026388
z.diff.lag1 -0.006698   0.093897  -0.071 0.943274
z.diff.lag2 -0.014133   0.093575  -0.151 0.880251
z.diff.lag3  0.144329   0.091552   1.576 0.118042
z.diff.lag4 -0.355845   0.091441  -3.892 0.000179

(Intercept) .
z.lag.1     *
z.diff.lag1
z.diff.lag2
z.diff.lag3
z.diff.lag4 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.9462 on 101 degrees of freedom
Multiple R-squared: 0.2521,	Adjusted R-squared: 0.215
F-statistic: 6.808 on 5 and 101 DF,  p-value: 1.647e-05


Value of test-statistic is: -2.2535 2.5438

Critical values for test statistics:
      1pct  5pct 10pct
tau2 -3.46 -2.88 -2.57
phi1  6.52  4.63  3.81

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